Nothing
set.seed(1)
#------------------------------------
# Design parameters
#------------------------------------
iterations <- 20000
beta <- c(0,1,0,0)
phi <- seq(-7L, 7L, 2) / 10L
rho <- seq(0.0, 0.8, 0.2)
tau1_ratio <- c(0.1, 0.5)
tau_corr <- 0
m <- 3:6
n <- c(8, 16)
print(lengths <- c(length(phi), length(rho), length(tau1_ratio), length(tau_corr), length(m), length(n)))
print(combos <- prod(lengths))
parms <- expand.grid(phi = phi, rho = rho, tau1_ratio = tau1_ratio, tau_corr = tau_corr, m = m, n=n)[sample(combos),]
head(parms)
#--------------------------------------------------------
# run simulations in parallel on Windows via SNOW
#--------------------------------------------------------
library(plyr)
library(snow)
library(foreach)
library(iterators)
library(doSNOW)
library(rlecuyer)
cluster <- makeCluster(parallel::detectCores(), type = "SOCK")
registerDoSNOW(cluster)
# set up parallel random number generator
clusterSetupRNGstream(cluster, 20131003)
# execute simulations
system.time(MB2_array <- maply(parms, .fun = simulate_MB2,
iterations = iterations, beta = beta,
.drop=FALSE, .parallel=TRUE,
.paropts = list(.packages="scdhlm")))
stopCluster(cluster)
##------------------------------------------------
## reshape and save results
##------------------------------------------------
library(reshape)
names(dimnames(MB2_array))[7:8] <- c("stat","moment")
MB2results <- cast(melt(MB2_array), ... ~ moment)
attr(MB2results, "iterations") <- iterations
attr(MB2results, "beta") <- beta
save(MB2results, file="data/MB2results.RData", compress="xz")
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